Abstract

Natriuretic peptides have multiple beneficial cardiovascular effects. Several recent studies have different findings about the N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in obese population. The primary purpose of this thesis is to investigate the relationship between the body mass index (BMI) and NT-proBNP concentrations before and after weight loss surgery. The secondary objective is to detect whether NT-proBNP has been correlated with other factors such as age, gender and diabetes status in obese patients. 132 obese subjects undergoing weight loss surgery with serial measurement of plasma N-terminal pro-B-type natriuretic peptide concentrations were collected by three different timepoints: preoperative, early (1 to 2 months), and late postoperative (6 months). Information such as race, gender and age was collected and used to understand the demographic importance in regards to affect the NT-proBNP levels. In addition, time dependent variables such as heart rate, fasting insulin level and total cholesterol were measured along three different timepoints. These variables can be useful to understand the clinical characteristics of the study population before and after weight loss surgery which can be potentially affect the NT-proBNP levels. ^ In modeling the plasma NT-proBNP levels, the researcher investigated the following models: General Linear Model, General Linear Mixed Model, Generalized Linear Model, Generalized Linear Model with GEE method and Generalized Linear Mixed Model. Once this was completed, the standard models without repeated measures and the mixed models with repeated measures were compared using goodness of fit assessments. ^ In conclusion, the repeated measure models in this study demonstrate that obese patients have has a positive relationship between BMI and NT-proBNP concentration on the mean level for each timepoint by using repeated measures analysis. The plasma NT-proBNP levels also related to age, gender and diabetes status. ^ Overall, in repeated measures the assessment of the effectiveness of treatments is more sensitive by making it possible to measure how the treatment affects each individual. The repeated measure analysis can use a case as its own comparison, or control. It helps to keep the validity of the results higher while still allowing for smaller than usual subject groups.^